Protocols. We follow the protocols of LMNet [1]}, using the official dataset split to train and validate the network, using 8 residual images as the input of Enc-M and the range image with 5 input channels \((x, y, z, r, e)\)  as the input of Enc-A as described in Sec. REF .
The generation of the residual image is in line with [1]}.
Note that, our method does not use any semantic information of different classes to refine predictions, such as vehicle and buildings. This means that our method only needs the binary moving/non-moving labels for training.
